source-driven-development
/source-driven-development
Ground every framework decision in official documentation. Use when you want authoritative, source-cited code for any framework or library.
- Author
- v1truv1us ↗
- Repository
- ai-eng-system ↗
- Licence
- MIT
- Last repository change
- 09.08.2026
Assessment and security
- Files in this package
- 2
- Scripts
- 0
- HTML comments
- 0
- URLs in SKILL.md
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No signals detected. Repository changed on 09.08.2026, without references to retired models or APIs.
MIT, open: use and modify while retaining author attribution.
What it does and when to use it
Ground every framework decision in official documentation. Use when you want authoritative, source-cited code for any framework or library.
Original author description
Ground every framework decision in official documentation. Use when you want authoritative, source-cited code for any framework or library.
How it works
- Overview
- When to Use
- Process
- Source Quality Hierarchy
- Common Rationalizations
- Verification
- Anti-Rationalization Table
SKILL.md preview
--- name: source-driven-development description: Ground every framework decision in official documentation. Use when you want authoritative, source-cited code for any framework or library. metadata: category: model-invoked --- Default output: return only the result, blockers, and required evidence. Omit preambles, process narration, repeated context, confidence scores, and follow-up offers. Use at most five bullets unless a required artifact or schema needs more. # Source-Driven Development ## Overview Verify every framework or library decision against official documentation before implementing. Flag any decision that lacks a source. This skill prevents the agent from relying on outdated patterns, hallucinated APIs, or assumptions about library behavior. ## When to Use - Working with a framework or library you have not used recently - When API surface area is large or frequently changing - When the cost of a wrong assumption is high (auth, data, security) - When documentation lookup tools are available ## Process ### Step 1: Identify Framework Decisions Before writing code that depends on a library: - List every API call, configuration option, or pattern you plan to use - Note which ones you are confident about and which are assumptions ### Step 2: Verify Against Official Sources For each decision: - Look up the current documentation - Confirm the API exists and behaves as expected - Note the version the docs target - If you cannot find a source, flag it explicitly ### Step 3: Cite Sources In comments or design docs: - Reference the official doc URL or section - Note the library version - Flag anything that could not be verified ### Step 4: Flag Unverified Decisions Explicitly mark decisions that lack source confirmation: - `// UNVERIFIED: assuming X based on Y pattern` - These flags must be resolved before production use ## Source Quality Hierarchy 1. Official documentation (highest) 2. Official examples and repositories 3. Well-maintained community guides with dates 4. Stack Overflow with accepted answers and recent dates 5. AI-generated suggestions (lowest, must be verified) ## Common Rationalizations | Rationalization | Reality | |---|---| | "I know this library well enough" | Libraries change between versions. Confidence is not accuracy. | | "Looking up docs slows me down" | Debugging a wrong assumption is slower than verifying upfront. | | "The AI already knows the right API" | AI training data has a cutoff date. APIs change. | ## Verification - [ ] Every framework API call is verified against current docs - [ ] Unverified decisions are explicitly flagged - [ ] Library versions are documented - [ ] No code depends on hallucinated or outdated API behavior ## Anti-Rationalization Table | Excuse | Counter | |--------|---------| | "I know this library well enough" | Libraries change between versions. Confidence is not accuracy. | | "Looking up docs slows me down" | Debugging a wrong assumption is slower than verifying upfront. | | "The AI already knows the right API" | AI training data has a cutoff date. APIs change. Verify against current docs. | | "I'll verify after the implementation works" | If the API does not exist, the implementation will not work. Verify first. | | "Stack Overflow has the answer" | Stack Overflow answers may be outdated. Official docs are the source of truth. |
Files in this package (2)
- SKILL.md 3 KB
- evals/evals.json 2 KB
Versions
| Repository | Score | Licence |
|---|---|---|
| This page · v1truv1us/ai-eng-system | 100 | MIT |
| lucasouzadev/agent-kit-skill | 100 | MIT |
| FrancoStino/opencode-skills-collection | 100 | MIT |
| drvoss/everything-copilot-cli | 100 | MIT |
| t068580-ai/Ai-Cybersecurity | 100 | MIT |
| sickn33/agentic-awesome-skills | 100 | MIT |
| muhammadshaharyarnaeem/blackgoat-agentskills | 100 | MIT |
| vinvcn/addyosmani-agent-skills-zh | 100 | MIT |
| addyosmani/agent-skills | 100 | MIT |
Identical content appears in 1 other GitHub folders. We show one copy with the highest score.
Database snapshot: 13.11.2026 · package version 3e948dc7ac2f (SHA-256 digest of the entire package)
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